Neural network models can now recognise images, understand text, translate languages, and play many human games at human or superhuman levels. These systems are highly …
AJE Kell, JH McDermott - Current opinion in neurobiology, 2019 - Elsevier
Highlights•Deep neural networks (DNNs) now reach human-level performance on some perceptual tasks.•They show human-like error patterns and predict sensory cortical …
Neuroscience research is undergoing a minor revolution. Recent advances in machine learning and artificial intelligence research have opened up new ways of thinking about …
Abstract Systems neuroscience seeks explanations for how the brain implements a wide variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to …
M Van Gerven, S Bohte - Frontiers in Computational Neuroscience, 2017 - frontiersin.org
Conclusion Neural networks are experiencing a revival that not only transforms AI but also provides new insights about neural computation in biological systems. The contributions in …
RM Cichy, D Kaiser - Trends in cognitive sciences, 2019 - cell.com
Artificial deep neural networks (DNNs) initially inspired by the brain enable computers to solve cognitive tasks at which humans excel. In the absence of explanations for such …
Highlights•Artificial and biological neural networks can be analyzed using similar methods.•Neural analysis has revealed similarities between the representations in artificial …
Neuroscience and artificial intelligence (AI) share a long history of collaboration. Advances in neuroscience, alongside huge leaps in computer processing power over the last few …
Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend …